Top Data & Analytics Jobs

Advise business and company functions using performance metrics and population analysis to drive strategy, maximize profit and minimize loss within risk limits. Lead adoption of analytic tools/methods, ensure compliance, manage project updates, budgets and forecasts, support quarterly/annual planning, and collaborate with mid-to-senior managers. Hybrid role with up to two remote days; in-person presence required.

Lead development and delivery of advanced analytics linking customer technology adoption to measurable outcomes (safety, productivity, efficiency, ROI). Provide KPI reporting, build dashboards, quantify customer value, and partner with commercial, product, digital, and field teams to drive adoption and translate insights into strategic, customer-facing recommendations.

Develop and validate commercial credit risk models (rating, loss forecasting, stress testing, pricing). Collaborate with business, data infrastructure, and governance teams to deploy, monitor, and document cloud-based model solutions and derive business insights from large datasets.

Design, develop, and optimize complex enterprise data warehouses and ETL architectures to support BI applications. Analyze BI data and advise on warehouse growth and integration. Collaborate with IT and business stakeholders to define requirements, ensure data quality and integrity, and lead implementation and integration efforts while providing technical guidance and alignment with architecture and BI needs.

As a Quantitative Research Engineer, design, develop, and implement software for automated trading systems using advanced statistical techniques. Collaborate with researchers and prioritize business needs.

Lead data science projects to optimize drug development using AI. Develop models for patient selection and clinical trial evaluations while collaborating with cross-functional teams to drive insights.

Use advanced analytics and ML to design and monitor credit risk models, optimize underwriting and credit strategies, partner with Engineering/Product/Compliance, oversee portfolio performance and regulatory alignment, and lead cross-functional initiatives to balance growth, compliance, and risk mitigation.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

Lead analytical studies to enhance Snap's SMC business, mentor a team of analysts, and develop data-driven strategies to inform growth and sales decisions.

Lead reporting and analytics for a business domain during a multi-year transformation. Own data migration, define business requirements, prioritize reporting roadmap, partner with tech/data teams and vendors, deploy reporting/analytics solutions (including ML-driven automation), measure KPIs, and drive adoption and value realization across cross-functional stakeholders.

Lead reporting and analytics for the finance domain, translate business requirements to product and tech teams, own data migration and roadmap, ensure data quality, enable data-driven automation and ML, coordinate organizational readiness for reporting transition, and manage stakeholder communications to deliver measurable business outcomes.

Lead reporting and analytics for a Business Transformation domain, owning data migration, roadmap, and stakeholder liaison. Define business requirements for reporting, ensure data quality, partner with tech and vendors, and drive data-driven automation and ML features to improve operations. Manage tools, KPIs, and change adoption across a multi-brand retail environment for the duration of a multi-year transformation.

The EO Imagery Analyst will provide geospatial and imagery analysis to improve data operations for ML algorithm testing, working with EO imagery products and metadata.

The Geospatial SAR Imagery Analyst Scientist analyzes SAR data to improve machine learning algorithms, curating imagery for data sets and recommending strategies for data gaps.

The EO Imagery Geospatial Analyst/Scientist provides geospatial expertise, conducts assessments, analyzes data formats, and supports ML algorithm testing.

Develop and deploy advanced statistical and ML models on large-scale alternative datasets to generate investable signals, partner with investment teams, evaluate data quality, and drive novel data-driven research with commercial impact.

Curate, cleanse, validate, and maintain large US equity and options datasets; integrate fundamental and alternative data; build data pipelines for research and trading; perform statistical and ML analysis to identify market patterns; document data provenance and collaborate with engineers and traders to deploy production-grade models.

Responsible for validating market risk models and ensuring their accuracy. Engage with various stakeholders, communicate findings, and maintain model integrity while leveraging innovative analytical technologies.

Senior Solution Architect responsible for strategy, solution and data architecture across application, platform, and data domains. Designs scalable architectures, data models, integration patterns, and data platforms (warehouses, lakes, streaming, cloud). Partners with business and engineering teams to ensure architectures meet functional, nonfunctional, governance, security, and regulatory requirements while enabling analytics, AI/ML, and transformation.

Lead a global analytics team to transform financial and operational data into actionable insights. Partner with stakeholders to align analytics with strategy, build scalable Power BI dashboards integrated with Snowflake, apply predictive modeling and ML, enforce data governance, drive automation with Python and Power Automate, and improve data architecture and reporting to inform decision-making and business performance.

Develop and validate market and counterparty credit risk models (VaR, Greeks, PFE, CVA) for Capital Markets. Collaborate with business partners to build cloud-based, ML-enabled analytical solutions, automate processes, communicate results, and own model development from concept through deployment and monitoring.

The Ticketing Insights Analyst II analyzes complex ticketing data to improve operational efficiency and customer experience through automation and data storytelling while collaborating with various teams to drive insights.

Lead enterprise data architecture efforts to design, govern, and operationalize trusted data assets. Define metadata, lineage, quality, and ETL/ELT patterns for data warehouses, lakes, and analytics; partner with engineering, risk, and business teams to ensure regulatory compliance, scalability, and BI/reporting enablement.

Lead end-to-end people analytics: frame problems, source and validate data, design methodologies, build advanced analytics/AI models, deliver executive-ready insights, partner with HR/Finance, and ensure data governance and privacy compliance.

Develop and implement software solutions for automated trading systems, working with quantitative researchers on complex financial challenges.